300-640認證考試資料匯總

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Cisco 300-640 Exam Syllabus Topics:

Section	Weight	Objectives
AI Infrastructure Security and Compliance	10%	- Access Control and Authentication - Security Best Practices - Compliance Considerations
AI Infrastructure Deployment	25%	- Network Switch Configuration - Cabling and Connectivity - Storage Configuration for AI - GPU Server Configuration - Hardware Installation and Configuration
AI Infrastructure Fundamentals	15%	- AI Ecosystem Components - GPU Architecture and Types - AI Workload Characteristics - AI Infrastructure Requirements
AI Infrastructure Operations	20%	- Monitoring and Management Tools - Capacity Planning - Performance Optimization - Troubleshooting Common Issues
Cisco AI Infrastructure Architecture	30%	- Network Architecture for AI Workloads - Storage Architecture Considerations - Hyperconverged Infrastructure for AI - Cisco UCS AI Infrastructure Solutions

>> 300-640软件版 <<

最新的300-640软件版 & Cisco 300-640考試：Implementing Cisco Data Center AI Infrastructure成功通過

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最新的 CCNP Data Center 300-640 免費考試真題 (Q32-Q37):

問題 #32
To support growing AI workload requirements, a regional medical practice is adding new X9516 X-Fabric module, UCS PCI Mezz cards, and UCS X580p PCIe nodes to their existing X-Series chassis. Which two administrative actions must be taken before the X-Fabric module is added to the chassis? (Choose two.)

A. Power down all IFMs in the chassis.
B. Power down all blades that would connect to the X-Fabric modules.
C. Disconnect device connector.
D. Install UCS PCI Mezzanine cards in X-Series blades.
E. Disconnect cabling between IFMs and fabric interconnects.

答案：B,D

解題說明：
Before adding the X9516 X-Fabric module, the affected X-Series blades must be powered down because the X-Fabric connectivity path requires hardware installation and cannot be safely introduced while the connected compute nodes are running. The UCS PCI Mezzanine cards must also be installed in the blades so they can physically connect through the X-Fabric module to the X580p PCIe nodes for GPU expansion.

問題 #33
Which components are part of the HyperFabric AI solution?

A. Cisco UCS servers combined with high-speed networking switches and third-party storage
B. Cisco UCS servers with NVIDIA GPUs, switches, optional VAST Data Storage and cloud- managed networking
C. integrated compute and networking hardware optimized for AI workloads, with optional cloud management
D. combination of Cisco networking hardware and software-defined storage designed for AI scalability

答案：B

解題說明：
HyperFabric AI combines Cisco UCS servers with NVIDIA GPUs, Cisco Nexus 6000 Series switches, optional VAST Data storage, and cloud-managed networking to provide an integrated AI infrastructure solution for training and inference workloads.

問題 #34
A network engineer analyzes RoCEv2 traffic flows in an AI training cluster and notices that all RoCEv2 packets have the Don't Fragment bit set in the IP header. Why must RoCEv2 set the DF bit in all packets?

A. to indicate to intermediate switches that the packet contains RDMA traffic requiring special handling
B. to ensure that packets always take the same path through ECMP routing for consistent latency
C. to enable Path MTU Discovery so that the optimal packet size can be negotiated
D. to prevent IP fragmentation that would break the InfiniBand sequence numbering and ordering guarantees

答案：D

解題說明：
RoCEv2 carries InfiniBand transport semantics over UDP/IP, and IP fragmentation would disrupt the expected packet sequencing and ordering behavior required by RDMA. Setting the Don't Fragment bit prevents intermediate devices from fragmenting RoCEv2 packets, preserving reliable RDMA transport behavior across the AI training fabric.

問題 #35
What is a function of NVLink technology within a high-performance AI server or cluster?

A. to manage power distribution and thermal regulation across all installed GPU units
B. to provide a high-speed, low-latency direct interconnect for GPU-to-GPU communication
C. to enable remote access and virtualization of GPU resources for distributed AI development teams
D. to establish a secure, encrypted channel for data transfer between the AI server and external storage

答案：B

解題說明：
NVLink provides a high-bandwidth, low-latency direct interconnect between GPUs. In AI servers and clusters, it accelerates GPU-to-GPU communication for training and inference workloads by allowing GPUs to exchange data much faster than through standard PCIe paths.

問題 #36
During validation testing, an engineer observes microbursts causing packet drops on GPU uplinks. Which monitoring capability best detects short-duration congestion events?

A. Daily syslog review
B. Streaming telemetry with high-frequency sampling
C. Manual CLI inspection once per week
D. NetFlow with hourly exports

答案：B

解題說明：
Microbursts occur within milliseconds and are often missed by traditional monitoring methods.
High-frequency streaming telemetry provides granular visibility into queue depth, drops, and latency conditions in real time. Hourly exports and infrequent manual inspection cannot reliably detect transient AI fabric congestion events.

問題 #37
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